[Show abstract][Hide abstract] ABSTRACT: The current findings completely affirm the validity of our original observations indicating the appropriateness of grouping primary breast cancer patients into those with negative, 1 to 3, or greater than or equal to 4 positive nodes. Results, however, reveal that there is a risk in combining all patients with greater than or equal to 4 positive nodes into a single group. Since there was a 25% greater disease-free survival and an 18% greater survival in those with 4 to 6 than in those with greater than or equal to 13 positive axillary nodes, such a unification may provide misleading information regarding patient prognosis, as well as the worth of a therapeutic regimen when compared with another from a putatively similar patient population. Of particular interest were findings relating the conditional probability, i.e., the hazard rate, of a treatment failure or death each year during the 5-year period following operation to nodal involvement with tumor. Whereas the hazard rate for those with negative, or 1 to 3 positive nodes, was relatively low and constant, in those with greater than or equal to 4 positive nodes the risk in the early years was much greater, but by the fifth year it was similar to that occurring when 1-3 nodes were involved, and not much different from negative node patients. The same pattern existed whether 4 to 6 or greater than or equal to 13 nodes were positive. When the current findings are considered relative to other factors with predictive import, it is concluded that nodal status still remains the primary prognostic discriminant.
Cancer 12/1983; 52(9):1551-7. DOI:10.1002/1097-0142(19831101)52:93.0.CO;2-3 · 4.89 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The National Cancer Institute and the Health Care Financing Administration share a strong research interest in cancer costs, access to cancer prevention and treatment services, and cancer patient outcomes. To develop a database for such research, the two agencies have undertaken a collaborative effort to link Medicare Program data with the Surveillance, Epidemiology, and End Results (SEER) Program database. The SEER Program is a system of 9 population-based tumor registries that collect standardized clinical information on cases diagnosed in separate, geographically defined areas covering approximately 10% of the US population. Using a deterministic matching algorithm, the records of 94% of SEER registry cases diagnosed at age 65 or older between 1973 to 1989, or more than 610,000 persons, were successfully linked with Medicare claims files. The resulting database, combining clinical characteristics with information on utilization and costs, will permit the investigation of the contribution of various patient and health care setting factors to treatment patterns, costs, and medical outcomes.
Medical Care 09/1993; 31(8):732-48. DOI:10.1097/00005650-199308000-00006 · 3.23 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: To compare male and female breast cancer and to determine the predictors of tumor characteristics and survival in both genders.
Male (n = 2923) and female breast cancer cases (n = 442,500) from the Surveillance, Epidemiology and End Results (SEER) registry were analyzed. Joinpoint regression was performed to detect changes in incidence trends from 1973 to 2001. Multiple logistic regression was used to regress each of four outcome variables (STAGE, LATERALITY, ESTROGEN, and PROGESTERONE RECEPTOR STATUS) on four demographic variables. Cox proportional hazards regression modeling was used to determine significant predictors of death of breast cancer after adjusting for demographic factors.
Both men and women aged less than 50 years were at higher risk for advanced breast cancers. Males were at higher risk than females for advanced tumors among non-whites. The risk of breast cancer death among all cases was lower for each 10-year increase in age by 2%, higher for those who are unmarried than for those who are married by 12% and 13% higher for non-whites than for whites.
Some important gender differences were detected with respect to factors associated with tumor characteristics, but gender was not a significant predictor of survival after adjusting for the other demographic variables.
Annals of Epidemiology 12/2005; 15(10):773-80. DOI:10.1016/j.annepidem.2005.01.001 · 2.00 Impact Factor
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